1,720,983 research outputs found
A Machine Learning Approach for the Simultaneous Prediction of Dynamic Modulus and Phase Angle of Asphalt Concrete Mixtures
No full textRoad pavements represent the backbone of every road network. Asphalt concrete (AC) mixtures are the main technological solution for road pavement construction. Their composition must be optimized to ensure adequate structural and functional performance. One of the most reliable parameters for the characterization of AC mixtures’ viscoelastic behavior is called complex modulus. Such a stiffness property is crucial in the evaluation of pavements’ mechanical performance. The complex modulus is usually described in terms of dynamic modulus and phase angle and, to be determined, long and expensive experimental campaigns must be carried out. An interesting alternative is represented by machine learning models that could provide fast and reliable predictions if properly trained on meaningful datasets. In this paper, the results of an extensive 4-point bending test laboratory investigation are thoroughly discussed and an up-to-date artificial neural network (ANN) methodology is outlined to simultaneously predict the dynamic modulus and the phase angle of nine different AC mixtures. To summarize the performance achieved by the developed model, six different metrics were evaluated. The empirical Witczak 1-37A equation, a well-established regression model, was used as a reference to compare the performance obtained by the neural modeling in terms of dynamic modulus. Machine learning predictions showed remarkable accuracy, outperforming regression-based ones with respect to all the evaluation metrics used. Both in terms of dynamic modulus and phase angle, Pearson correlation coefficients and coefficients of determination achieved by the ANN model were higher than 0.98, resulting in a powerful and reliable predictive tool
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Improved predictions of asphalt concretes’ dynamic modulus and phase angle using decision-tree based categorical boosting model
Full text linkThe most suitable parameter to summarize the viscoelastic response of asphalt concrete (AC) mixtures is the complex modulus, defined by means of its two main components: the dynamic modulus E∗ and the phase angle φ. They are frequently determined by means of expensive and time-consuming laboratory procedures that require suitable equipment and high-skilled technicians. As an alternative, machine learning models can be trained to make very accurate predictions and thus, substitute at least some of these lab tests. This study proposes an innovative Categorical Boosting (CatBoost) approach for the simultaneous prediction of both E∗ and φ. Nine different AC mixtures were prepared, and an extensive 4-point bending test (4PBT) experimental campaign was carried out under ten loading frequencies and six testing temperatures. In order to thoroughly compare the developed model with two well-established empirical equations (Witczak-Fonseca and Witczak 1–37A), the same input features were selected. Pre-processing and resampling techniques were implemented to both reduce computational effort and improve model efficiency, whereas an in-depth sensitivity analysis was also performed. The entire methodology was implemented in Python 3.8.5. Six different goodness-of-fit metrics were used to robustly evaluate the performance of the developed CatBoost model and to compare it with the results of two regression-based models and a reference state-of-the-art artificial neural network (SoA-ANN). Findings showed that both machine learning (ML) models outperformed the regression-based ones, displaying significantly better performance for all metrics used. CatBoost and SoA-ANN showed roughly comparable results, characterized by a mean coefficient of determination (R2) slightly higher than 0.98. Since goodness-of-fit metrics resulted in no marked differences between machine learning models, CatBoost approach might be preferred because of its easy implementation in Python and its high interpretability. Within the context of pavement engineering, such an advanced machine learning model could provide a useful and powerful tool for asphalt mixtures’ design applications
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Recommendations of RILEM TC 252-CMB on the Effect of Short Term Aging Temperature on Long Term Properties of Asphalt Binder
No full textThe Rilem Technical Committee on Chemo Mechanical Characterization of Bituminous Materials has investigated the effect of short term aging tempera-ture on long term properties of asphalt binder, chemically, physically and mi-crostructurally. The increased use of warm mix asphalt (WMA) technologies warrants such investigations in order to validate laboratory aging procedures. To this end, penetration, softening point, Fourier Transform Infrared Spec-troscopy, dynamic shear rheology (DSR) and electron microscopy (ESEM) were used. The experimental results on binders and warm (WMA) and hot (HMA) mixtures from nine participating laboratories indicate that the binder source, as well as method of evaluation, result in different rankings and be-haviors among the four binders used. The TC recommends the development of appropriate RTFOT aging temperatures for the simulation of binder aging in WMA
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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